Papers

2

Total Citations

5

H-Index

2

About

Dr. Michelle Daniel is a leading researcher in computational pathology and multi-modal imaging, with a primary focus on unraveling the tumor microenvironment (TME) in large-scale cancer studies. Her major contributions center on developing robust, scalable image analysis pipelines that integrate diverse imaging modalities—such as multiplexed immunofluorescence and histology—to characterize immune cell interactions and tissue architecture across thousands of patients. Dr. Daniel is a key figure in the IMMUcan consortium, where her work enables the integrated immunoprofiling of massive adaptive cancer cohorts, moving beyond small patient samples to population-level insights. Her most cited papers, including her 2025 work on multi-modal analysis for large-scale cancer tissue studies (garnering early attention with 3 and 2 citations), lay the methodological groundwork for linking TME features to patient prognosis. By tackling the computational challenges of processing high-dimensional, multi-center data, Dr. Daniel’s research directly supports the discovery of novel biomarkers and therapeutic targets. Her achievements are pivotal for translating complex imaging data into clinically actionable knowledge, making her a vital contributor to the future of precision oncology.

Research Focus

Key Achievements

2
H-Index
2
Papers
5
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Multi-modal image analysis for large scale cancer tissue studies within IMMUcan
3 citations · 2025
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: University of Zurich, ETH Zurich

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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